Jurkat project
Juba
2026-01-13
Project description
We are studying the effect of an inhibitor of the cGAS-STING signaling pathway H151 on T-ALL model cell line Jurkat.
The biological experiment revealed that H151 causes cell death, so the pathway is important for survival of T-ALL.
We want to explore the differential expressed genes between normal condition and by inhibiting the pathway. Thus we are going to perform a differential expression analysis (DEA) followed by a pathway enrichment analysis (PEA)
Following a basic RNA-seq pipeline analysis
Importing data
Raw counts
Metadata
Experimental data
Data exploration
First let’s view the distribution of the different bio types we have in our data :
In the downstream analysis (DEA), we’ll
be focusing on the top 2 biotypes (protein_coding and
lncRNA). Additional filtering will be applied :
MaxCount_threshold= 20 (At least 1 sample must have a read count over that value)CpmCount_threshold= 0.5 (Count per million reads threshold)MinSample= 3 (Samples that should pass the cpm threshold)
Now to understand the global gene expression landscape and to assess the quality control of our data, we need to perform a dimentionality reduction analysis : Principal component analysis (PCA)
The PCA :
- Assumes homoscedasticity (equal variance) between the samples
- Assumes roughly normal distribution
So we need to perform some data transformation first on
raw counts.
We’ll be using a Variance Stabilizing
Transformation (VST) from the DESeq2 package. And
This will :
- Normalize for library size (
DESeq2computes size factors using amedian-of-ratiosmethod) - Use a negative binomial model to estimate dispersion
- Apply a variance-stabilizing mathematical transformation
Differential expression analysis (DEA)
Now let’s dive into gene expression.
dds <- pre_process_results$DESeqData
dds$Condition <- relevel(dds$Condition, ref = "Jurkat_ct") ## set the control
dds <- DESeq(dds) Let’s get a quick overview of the distribution of the DEGs
- Volcano plot:
- Heatmap:
Let’s draw a heatmap of the top 20up and 20down genes
DEGs list overview
- Up regulated genes: 261
1- protein-coding genes
## [1] "CXCR3" "APLN" "H2BC21" "RGS6"
## [5] "BHLHE40" "COL6A3" "VGF" "SLAMF8"
## [9] "KANK4" "WNT8B" "TMEM240" "MSLNL"
## [13] "TMEM163" "NANOS1" "RPRML" "CCR8"
## [17] "KIT" "TMEM269" "TERT" "CLEC12A"
## [21] "RNASEH2A" "DTL" "UNG" "MCM4"
## [25] "TCHH" "LVRN" "GPR146" "ENSG00000289128"
## [29] "CXXC4" "REEP1" "LRRC10B" "DDIT4"
## [33] "H4C9" "TINCR" "DDT" "SCLY"
## [37] "HERC3" "PTPN6" "SLC37A2" "TRARG1"
## [41] "DENND2D" "TMEM255B" "PCNA" "GET1"
## [45] "MYT1L" "UHRF1" "C1S" "ELFN2"
## [49] "FAM81A" "SASH3" "JAKMIP1" "TWIST1"
## [53] "ABTB3" "ADGRL2" "MYO18B" "ENSG00000102409"
## [57] "CSPG5" "LNP1" "GNA15" "MCM2"
## [61] "P2RX6" "FA2H" "MCM3" "OPN3"
## [65] "SLBP" "NECAB3" "EID2B" "PDE4A"
## [69] "MCM7" "IGLL1" "NOTCH1" "PPM1H"
## [73] "PDXP" "JMJD7" "DTX1" "CALML4"
## [77] "FEN1" "RMI2" "KRT72" "HK2"
## [81] "GNMT" "TCF7" "PIGW" "ATP2B2"
## [85] "IMPDH2" "ZNF704" "H3C10" "OXTR"
## [89] "PANO1" "FBXL22" "TTC7A" "NT5DC2"
## [93] "POLG" "NPIPB13" "ANKRD37" "NUP210"
## [97] "WT1" "ZMYND19" "RHPN2" "CXXC5"
## [101] "NCBP2AS2" "NPIPB11" "GNG4" "NOTCH2NLB"
## [105] "IVNS1ABP"2- lncRNA genes
## [1] "MIR210HG" "ENSG00000288930" "RANBP3-DT" "IRAIN"
## [5] "ENSG00000196465" "ENSG00000181577" "ENSG00000146223" "LINC00484"
## [9] "ENSG00000125651" "ENSG00000211454" "ENSG00000236204" "ENSG00000213139"
## [13] "LINC01963" "ENSG00000170571" "ENSG00000086300" "ENSG00000136840"
## [17] "ENSG00000290124" "ENSG00000269968" "ENSG00000230148" "ILF3-DT"
## [21] "ENSG00000173914" "ENSG00000171357" "ENSG00000138614" "PKD1P6-NPIPP1"
## [25] "ENSG00000261226" "ENSG00000183979" "ENSG00000165028" "ENSG00000182197"
## [29] "ASH1L-AS1" "ENSG00000205903" "TOLLIP-DT" "MIF4GD-DT"
## [33] "ENSG00000272356" "ZNF674-AS1" "ENSG00000198034" "ENSG00000143971"
## [37] "YTHDF3-DT" "ENSG00000287362" "ENSG00000277767" "FAM30A"
## [41] "ENSG00000233178" "ENSG00000276390" "ENSG00000187164" "ENSG00000142556"
## [45] "ENSG00000124370" "ENSG00000167863" "ENSG00000224066" "ENSG00000151093"
## [49] "ENSG00000165475" "C16orf95-DT" "ENSG00000289985" "ZNF346-IT1"
## [53] "ENSG00000259736" "ENSG00000288586" "ENSG00000278611" "ENSG00000140092"
## [57] "ENSG00000231527" "FOXD2-AS1" "LINC00641" "LRRC8D-DT"
## [61] "NIPBL-DT" "ENSG00000138738" "ENSG00000251247" "ENSG00000183891"
## [65] "ENSG00000163935" "PRKCZ-AS1" "SLFNL1-AS1" "ENSG00000137941"
## [69] "SLC16A4-AS1" "ZNF710-AS1" "MAD2L1-DT" "ENSG00000260442"
## [73] "ENSG00000244184" "GJD3-AS1" "TBC1D22A-DT" "ENSG00000157800"
## [77] "ENSG00000126107" "MHENCR" "ENSG00000197548" "ENSG00000133794"
## [81] "SNHG10" "C9orf163" "ENSG00000175040" "ENSG00000143740"
## [85] "ENSG00000105808" "RASSF1-AS1" "ENSG00000178982" "ENSG00000185621"
## [89] "PDK1-AS1" "ENSG00000291056" "SUGT1-DT" "ENSG00000124140"
## [93] "LINC01311" "ENSG00000285437" "ENSG00000100003" "NKILA"
## [97] "ENSG00000243479" "ENSG00000100321" "ENSG00000287104" "ENSG00000158555"
## [101] "ENSG00000153936" "MCPH1-DT" "RNF139-DT" "ENSG00000173218"
## [105] "ENSG00000155366" "ENSG00000267757" "ENSG00000055950" "ENSG00000162413"
## [109] "MCF2L-AS1" "ENSG00000246308" "ENSG00000065413" "ENSG00000113595"
## [113] "LINC01284" "ENSG00000139266" "ENSG00000153561" "ENSG00000118242"
## [117] "GABPB1-IT1" "CIRBP-AS1" "ENSG00000267688" "ENSG00000114019"
## [121] "LINC01971" "ENSG00000068394" "ENSG00000185885" "PARTICL"
## [125] "LINC00235" "MIR193BHG" "ST3GAL1-DT" "ENSG00000196810"
## [129] "ENSG00000286548" "ENSG00000006194" "PAXIP1-DT" "ENSG00000106336"
## [133] "LINC00528" "CNN3-DT" "ENSG00000198353" "ENSG00000108479"
## [137] "PRKCH-AS1" "ENSG00000221823" "ENSG00000165915" "ENSG00000160867"
## [141] "LINC02019" "YEATS2-AS1" "STAM-DT" "ENSG00000104219"
## [145] "LINC00304" "RORB-AS1" "ENSG00000149823" "LINC01422"
## [149] "ENSG00000177556" "DNAH10OS" "LINC01389" "ENSG00000101336"
## [153] "ENSG00000276853" "ENSG00000213047" "LINC02918" "DANCR"- Down regulated genes: 650
1- protein-coding genes
## [1] "CEP126" "ZNF836" "SLC26A11" "CLEC18B" "PCDHGA6" "SLC8A2"
## [7] "PLCD1" "RNFT1" "RELB" "ZBTB7B" "ANKRD31" "PCYT1B"
## [13] "MACO1" "NQO2" "NIPAL1" "PLTP" "ZNF585B" "NPIPA5"
## [19] "STPG1" "DMGDH" "CFAP69" "ZNF329" "APOBEC3G" "CLIC4"
## [25] "C2orf50" "SERPINI1" "B3GNT5" "PLEKHA6" "GDPD1" "MAP1A"
## [31] "GABRB2" "DUSP16" "CCT6B" "GARIN1A" "ACTRT3" "ELL2"
## [37] "BCHE" "SHF" "TCP11L2" "ARMH4" "TMEM79" "TSPAN10"
## [43] "PEX5L" "MYO5B" "TBC1D30" "FGF22" "RGPD3" "ANG"
## [49] "SPRY3" "IFI35" "DOK4" "IFRD1" "CASP9" "CNGA1"
## [55] "SPTB" "ZNF610" "C3AR1" "PCDHGA10" "ERRFI1" "FRRS1"
## [61] "TNS2" "MPZL3" "TSNAXIP1" "EGFL7" "SCG2" "SLC16A9"
## [67] "DENND2C" "RSPH4A" "SLC17A7" "FZD7" "MCTP1" "HOXB6"
## [73] "WNK4" "RAB39B" "NUDT13" "LRP12" "CYP2J2" "WDR31"
## [79] "CTSG" "ID1" "SLCO3A1" "SYNE4" "CD84" "SLC38A3"
## [85] "FAM219A" "CYSRT1" "SERTAD1" "DNAAF8" "LAT2" "CA13"
## [91] "DNAJC3" "TNN" "ERBB2" "CAPS" "JAM2" "ULBP2"
## [97] "RXRA" "FLVCR2" "PILRA" "C11orf65" "SPNS3" "ICOS"
## [103] "CBS" "EVI2A" "RTN2" "ADAM8" "IL20RB" "BEND6"
## [109] "FTH1" "TMEM151A" "TMEM267" "GCNT4" "PEX11G" "C19orf38"
## [115] "DNAI7" "DDRGK1" "CCDC184" "P2RY10" "TMBIM1" "OASL"
## [121] "FOSB" "DBNDD1" "CCDC69" "NECTIN3" "JAML" "IRAK2"
## [127] "EFNB2" "TAGLN" "BVES" "SYNGR4" "CACNG8" "CCNB3"
## [133] "FMO4" "PEAR1" "SLC43A1" "MIA2" "RAB17" "CDS1"
## [139] "EVA1B" "TPST1" "CYB5R1" "C14orf39" "NES" "APOL1"
## [145] "SSC4D" "TXNRD1" "C22orf23" "METTL27" "EHD2" "PDGFRL"
## [151] "MAML2" "ZNF235" "GAB2" "CGRRF1" "DAPP1" "LCA5L"
## [157] "DNAJB9" "IRAG2" "CCDC65" "GPT2" "SLC9A9" "WIPI1"
## [163] "EPHX1" "MN1" "SEL1L3" "NUTM2E" "RBP5" "BBC3"
## [169] "EPS8" "NEK5" "ASS1" "ARHGAP29" "RGS17" "EIF4EBP1"
## [175] "ABHD3" "TXK" "EID3" "CTSO" "PGGHG" "ACTN2"
## [181] "BMP10" "KIF5C" "CYP1A1" "MFAP3L" "TRIM22" "LAMC3"
## [187] "ZFP2" "ZNF582" "PCLO" "PLEKHH3" "EAF2" "NAGS"
## [193] "ATF3" "HSPA5" "HABP2" "GCLM" "HERPUD1" "IL23A"
## [199] "TIAM2" "TM6SF1" "DLL1" "ADGRB1" "SLC2A12" "TLR3"
## [205] "TLR5" "DGKG" "ASNS" "NKX2-2" "FAM43A" "IL15RA"
## [211] "PTGER3" "CDKN1A" "C7orf31" "FAAH2" "TFE3" "ABHD4"
## [217] "SLC48A1" "IRF7" "HRH1" "AMIGO2" "AARD" "CILP2"
## [223] "PCK2" "SMPDL3B" "DMRTA2" "TNFSF9" "UBXN8" "PSAT1"
## [229] "NPAS1" "CECR2" "EFNA1" "ENTPD1" "PLCL1" "CD55"
## [235] "PRG4" "SV2B" "CREB3L3" "REPS2" "ETFBKMT" "ISG20"
## [241] "PPFIBP2" "INCA1" "TMOD1" "ARRDC3" "SYT1" "SLC1A5"
## [247] "SESN2" "YPEL4" "ULBP1" "HRK" "PPP2R3A" "FRMD3"
## [253] "TCAF2" "NOS1AP" "DRC3" "RBM11" "SNAI1" "POF1B"
## [259] "SMTNL2" "NCF2" "ZNF880" "NCAM1" "TMEM200A" "LY9"
## [265] "IQUB" "MT1F" "DRAM1" "SMOX" "CLIP2" "CEBPB"
## [271] "TRPC5OS" "AMOT" "DAB1" "RASD1" "MET" "SGIP1"
## [277] "PHOSPHO1" "GABARAPL1" "NECTIN2" "IL7R" "CCER2" "FUT1"
## [283] "WNT10A" "MYH14" "NIBAN1" "TMEM217" "PLAU" "MYOM2"
## [289] "DEPTOR" "PMEL" "FLRT1" "SMAD7" "ADGRL3" "PRKG2"
## [295] "GLS2" "LDB3" "PCDHB14" "MPZ" "TMEM156" "TRAF3IP2"
## [301] "TLL1" "MFAP4" "MAFB" "SLC30A1" "TEX14" "KANK3"
## [307] "LPIN3" "THEMIS2" "SSC5D" "SHISA2" "FMN1" "SCN3A"
## [313] "LACC1" "LPAR4" "NDUFA4L2" "TMEM74B" "XKRX" "CDC20B"
## [319] "HYDIN" "PCDHGB7" "TBL1X" "ST8SIA6" "SCN3B" "RAD9B"
## [325] "ADGRE1" "STC2" "TLR1" "ITGB5" "JDP2" "NR2F2"
## [331] "CRPPA" "ERBB3" "CDNF" "ANXA3" "GBP2" "CALCRL"
## [337] "TNFRSF11A" "ZNF703" "CHRNB4" "ADM2" "HSPA12B" "TRPC1"
## [343] "LMX1B" "PTGES" "REXO5" "CATSPERG" "PCDHGB6" "CREB5"
## [349] "TEX19" "TGFBR3" "SLC45A1" "COLGALT2" "SYT11" "SH2D6"
## [355] "PCDH12" "RPS6KA2" "CST7" "DUSP8" "TREML2" "WDR93"
## [361] "PIFO" "CDH15" "TMIE" "HSPA1B" "CEACAM1" "SLC16A6"
## [367] "CCDC148" "ZNF35" "ZFPM2" "CFTR" "PCDH19" "SP140"
## [373] "GPAT3" "PPP1R15A" "FBXO39" "CXCL3" "TRAT1" "SLC3A2"
## [379] "SORBS1" "MTTP" "KIF17" "ADTRP" "ZBTB46" "RGS16"
## [385] "PIWIL4" "FLRT3" "JAKMIP2" "TMEM140" "SPTA1" "CSTA"
## [391] "TC2N" "SCN4B" "PLAC1" "JAKMIP3" "FOXA3" "PRDM1"
## [397] "HTR2B" "F2RL2" "NQO1" "SOX6" "PATJ" "CHAC1"
## [403] "GPR18" "FAM166B" "CRB3" "MKX" "TLR6" "SCN4A"
## [409] "CLCA1" "LY96" "IL31RA" "NYAP1" "DPP4" "TRPM6"
## [415] "CCPG1" "AKR1C3" "TRPS1" "CEACAM21" "IL12A" "ID2"
## [421] "OLAH" "MAP3K8" "GLIPR1" "TRIB3" "STYK1" "MATN4"
## [427] "BEST1" "CCDC110" "TSC22D3" "KCNN3" "FAM133A" "CLU"
## [433] "PDE11A" "ADRA1A" "JUN" "CHRNA6" "DDIT3" "LRRC2"
## [439] "HEPH" "ILDR1" "SATL1" "GPR132" "FOSL1" "XKR3"
## [445] "SLC6A9" "INPP5J" "GPX2" "AKR1C8" "CRIM1" "UEVLD"
## [451] "SLC7A11" "TSPAN19" "CYP19A1" "PANX2" "CD80" "BMP6"
## [457] "AKR1C2" "OSGIN1" "MMP8" "EGF" "HRG" "GDAP1L1"
## [463] "ABCC3" "UCP1" "HSPA6" "RHOB" "RASSF6" "HMOX1"
## [469] "C4orf17"2- lncRNA genes
## [1] "RAP2C-AS1" "DDX19A-DT" "SP2-DT" "ENSG00000204482"
## [5] "LINC01058" "LINC00652" "LINC01134" "LINC01215"
## [9] "LINC-PINT" "USP27X-DT" "ENSG00000289958" "RPAP3-DT"
## [13] "ENSG00000138061" "ENSG00000272438" "ERCC6L2-AS1" "PCAT1"
## [17] "ENSG00000102245" "SNRPA1-DT" "ACTR3-AS1" "ENSG00000261173"
## [21] "LINC01115" "CPEB1-AS1" "ENSG00000177788" "PRDM8-AS1"
## [25] "MIR4280HG" "LINC00662" "ENSG00000291010" "TWF2-DT"
## [29] "RORA-AS1" "ENSG00000178896" "COPB2-DT" "ZNF225-AS1"
## [33] "ENSG00000197024" "LNCRNA-IUR" "LINC01465" "LINC00853"
## [37] "MIR4435-2HG" "ENSG00000105698" "ENSG00000213588" "ENSG00000213465"
## [41] "FAM174A-DT" "ZNF451-AS1" "LINC02709" "HDAC2-AS2"
## [45] "ENSG00000260874" "ENSG00000125775" "PCOTH" "BAZ2B-AS1"
## [49] "BTG1-DT" "ENSG00000228436" "SDCBP2-AS1" "ENSG00000140104"
## [53] "ENSG00000108599" "ENSG00000275793" "TMEM254-AS1" "ENSG00000285706"
## [57] "ENSG00000288996" "HULC" "ALG1L9P" "ZFAND2A-DT"
## [61] "LINC01825" "RPL37A-DT" "SAMD12-AS1" "ENSG00000162543"
## [65] "LINC00877" "LYPLAL1-DT" "MKLN1-AS" "BTG2-DT"
## [69] "ENSG00000188761" "ENSG00000283141" "ECE1-AS1" "DLGAP1-AS2"
## [73] "WEE2-AS1" "ENSG00000021574" "OXR1-AS1" "LINC00680"
## [77] "ENSG00000289183" "ENSG00000273183" "SPOPL-DT" "LINC02901"
## [81] "LGALS8-AS1" "FBXO38-DT" "LINC01694" "ENSG00000102543"
## [85] "LINC00659" "ENSG00000204356" "ENSG00000198752" "MIR22HG"
## [89] "LINC00511" "ENSG00000243811" "LINC00239" "LINC00882"
## [93] "ENSG00000214770" "ENSG00000291136" "SLC12A5-AS1" "ENSG00000120071"
## [97] "MAGOH-DT" "MIAT" "YWHAH-AS1" "KRT10-AS1"
## [101] "ENO1-AS1" "LINC00685" "LINC01277" "ENSG00000291027"
## [105] "KDSR-DT" "ENSG00000006634" "ENSG00000160703" "TTTY14"
## [109] "LINC02265" "ENSG00000226029" "CEBPB-AS1" "ENSG00000159496"
## [113] "FKTN-AS1" "LINC01307" "ZNF516-AS1" "ENSG00000139800"
## [117] "LACTB2-AS1" "ENSG00000289115" "LINC02377" "ZBED3-AS1"
## [121] "ENSG00000214046" "ENSG00000115355" "ENSG00000161016" "LINC00029"
## [125] "ENSG00000119684" "RPL26L1-AS1" "PRRT3-AS1" "CBR3-AS1"
## [129] "JDP2-AS1" "ENSG00000172071" "ENSG00000110063" "PRMT5-DT"
## [133] "ENSG00000124172" "ENSG00000205643" "ENSG00000287808" "ENSG00000163794"
## [137] "GAS1RR" "ENSG00000149451" "ENSG00000284308" "ENSG00000135436"
## [141] "VLDLR-AS1" "ENSG00000227500" "ENSG00000180611" "LINC00992"
## [145] "UBQLN1-AS1" "ENSG00000157992" "LINC02341" "LINC02018"
## [149] "NQO1-DT" "LINC00648" "ENSG00000158406" "ENSG00000198888"
## [153] "ECI2-DT" "ERICH2-DT" "ENSG00000105516" "MDN1-AS1"
## [157] "ENSG00000254510" "LINC02321" "HIPK1-AS1" "ENSG00000196132"
## [161] "ENSG00000188739" "PRPF19-DT" "ENSG00000171735" "PCDH10-DT"
## [165] "ENSG00000219200" "ENSG00000132005" "LINC00632" "ROCK1P1"
## [169] "SLC26A4-AS1" "ENSG00000263528" "LUCAT1" "ENSG00000272010"
## [173] "ENSG00000259905" "ENSG00000163154" "LINC02561" "STX5-DT"
## [177] "LINC02539" "L3MBTL2-AS1" "ENSG00000290683" "LINC00365"
## [181] "NMRAL2P"Now inspecting the gene biotypes
Let’s inspect the top up and down genes deeper !
Pathway enrichment analysis (PEA)
Gene Ontology (GO)
NOTE:
For the downstream analysis, only protein_coding genes will
be kept to ensure the significance of the resulting terms!
We will be using first all the protein_coding DEGs (574)
then only Down-regulated one (469)
All DEGs
Let’s inspect the pathways enriched with all the DEGs (up & down)
that are protein_coding
Results
The top 40 most significant pathways enriched with these DEGs are
## [1] "leukocyte activation"
## [2] "lymphocyte activation"
## [3] "multicellular organismal-level homeostasis"
## [4] "regulation of cell activation"
## [5] "regulation of leukocyte activation"
## [6] "cell-cell adhesion"
## [7] "regulation of leukocyte differentiation"
## [8] "T cell activation"
## [9] "myeloid leukocyte activation"
## [10] "blood vessel morphogenesis"
## [11] "regulation of hemopoiesis"
## [12] "response to endoplasmic reticulum stress"
## [13] "vasculature development"
## [14] "response to lipid"
## [15] "negative regulation of immune system process"
## [16] "regulation of T cell mediated immunity"
## [17] "response to ketone"
## [18] "leukocyte differentiation"
## [19] "integrated stress response signaling"
## [20] "epithelial cell proliferation"
## [21] "blood vessel development"
## [22] "circulatory system process"
## [23] "response to organic cyclic compound"
## [24] "mononuclear cell differentiation"
## [25] "lymphocyte differentiation"
## [26] "endothelial cell migration"
## [27] "response to topologically incorrect protein"
## [28] "angiogenesis"
## [29] "regulation of lymphocyte differentiation"
## [30] "secretion"
## [31] "positive regulation of cytokine production"
## [32] "response to unfolded protein"
## [33] "inflammatory response"
## [34] "regulation of lymphocyte activation"
## [35] "secondary metabolic process"
## [36] "regulation of cell adhesion"
## [37] "tube morphogenesis"
## [38] "cell-cell adhesion via plasma-membrane adhesion molecules"
## [39] "hemopoiesis"
## [40] "immune effector process"The top 40 pathway with the highest
RichFactor (Count per pathway length ratio)
## [1] "double-strand break repair via break-induced replication"
## [2] "regulation of ferroptosis"
## [3] "regulation of heat generation"
## [4] "detection of molecule of bacterial origin"
## [5] "ferroptosis"
## [6] "DNA strand elongation involved in DNA replication"
## [7] "epithelial cell fate commitment"
## [8] "regulation of IRE1-mediated unfolded protein response"
## [9] "regulation of DNA-templated DNA replication initiation"
## [10] "negative regulation of endoplasmic reticulum unfolded protein response"
## [11] "heat generation"
## [12] "negative regulation of leukocyte chemotaxis"
## [13] "melanin biosynthetic process"
## [14] "melanin metabolic process"
## [15] "secondary metabolite biosynthetic process"
## [16] "integrated stress response signaling"
## [17] "regulation of T cell mediated cytotoxicity"
## [18] "secondary metabolic process"
## [19] "leukocyte activation involved in inflammatory response"
## [20] "negative regulation of chemotaxis"
## [21] "negative regulation of leukocyte migration"
## [22] "T cell mediated cytotoxicity"
## [23] "regulation of T cell mediated immunity"
## [24] "toll-like receptor signaling pathway"
## [25] "endoplasmic reticulum unfolded protein response"
## [26] "female gonad development"
## [27] "development of primary female sexual characteristics"
## [28] "response to unfolded protein"
## [29] "macrophage activation"
## [30] "positive regulation of tumor necrosis factor superfamily cytokine production"
## [31] "response to topologically incorrect protein"
## [32] "T cell mediated immunity"
## [33] "negative regulation of immune effector process"
## [34] "response to glucocorticoid"
## [35] "myeloid leukocyte activation"
## [36] "response to ketone"
## [37] "homophilic cell adhesion via plasma membrane adhesion molecules"
## [38] "response to corticosteroid"
## [39] "negative regulation of leukocyte activation"
## [40] "regulation of lymphocyte differentiation"Dotplot
Cnet plot
Down DEGs
Results
The top 50 most significant pathways enriched with these DEGs are
## [1] "leukocyte activation"
## [2] "response to endoplasmic reticulum stress"
## [3] "regulation of cell activation"
## [4] "cell-cell adhesion"
## [5] "multicellular organismal-level homeostasis"
## [6] "lymphocyte activation"
## [7] "regulation of leukocyte activation"
## [8] "integrated stress response signaling"
## [9] "myeloid leukocyte activation"
## [10] "response to lipid"
## [11] "response to topologically incorrect protein"
## [12] "response to unfolded protein"
## [13] "circulatory system process"
## [14] "T cell activation"
## [15] "endothelial cell migration"
## [16] "regulation of T cell mediated immunity"
## [17] "cell-cell adhesion via plasma-membrane adhesion molecules"
## [18] "regulation of leukocyte differentiation"
## [19] "positive regulation of response to external stimulus"
## [20] "toll-like receptor signaling pathway"
## [21] "response to nutrient levels"
## [22] "negative regulation of immune system process"
## [23] "homophilic cell adhesion via plasma membrane adhesion molecules"
## [24] "regulation of ferroptosis"
## [25] "endoplasmic reticulum unfolded protein response"
## [26] "regulation of T cell mediated cytotoxicity"
## [27] "leukocyte activation involved in inflammatory response"
## [28] "response to ketone"
## [29] "regulation of response to biotic stimulus"
## [30] "regulation of heat generation"
## [31] "detection of molecule of bacterial origin"
## [32] "ferroptosis"
## [33] "leukocyte differentiation"
## [34] "inflammatory response"
## [35] "positive regulation of cytokine production"
## [36] "macrophage activation"
## [37] "viral entry into host cell"
## [38] "cell junction organization"
## [39] "T cell mediated immunity"
## [40] "regulation of hemopoiesis"
## [41] "response to molecule of bacterial origin"
## [42] "regulation of IRE1-mediated unfolded protein response"
## [43] "entry into host"
## [44] "positive regulation of defense response"
## [45] "regulation of cell adhesion"
## [46] "cellular response to unfolded protein"
## [47] "blood circulation"
## [48] "blood vessel morphogenesis"
## [49] "negative regulation of cell activation"
## [50] "T cell mediated cytotoxicity"The top 50 pathway with the highest
RichFactor (Count per pathway length ratio)
## [1] "regulation of ferroptosis"
## [2] "regulation of heat generation"
## [3] "detection of molecule of bacterial origin"
## [4] "ferroptosis"
## [5] "natural killer cell mediated cytotoxicity directed against tumor cell target"
## [6] "regulation of natural killer cell mediated immune response to tumor cell"
## [7] "anterograde dendritic transport"
## [8] "regulation of IRE1-mediated unfolded protein response"
## [9] "negative regulation of endoplasmic reticulum unfolded protein response"
## [10] "heat generation"
## [11] "positive regulation of chondrocyte differentiation"
## [12] "PERK-mediated unfolded protein response"
## [13] "IRE1-mediated unfolded protein response"
## [14] "regulation of translation in response to stress"
## [15] "regulation of cardiac muscle cell differentiation"
## [16] "integrated stress response signaling"
## [17] "negative regulation of T cell mediated immunity"
## [18] "positive regulation of cartilage development"
## [19] "regulation of endoplasmic reticulum unfolded protein response"
## [20] "regulation of T cell mediated cytotoxicity"
## [21] "leukocyte activation involved in inflammatory response"
## [22] "negative regulation of response to endoplasmic reticulum stress"
## [23] "regulation of acute inflammatory response"
## [24] "microglial cell activation"
## [25] "amino acid import across plasma membrane"
## [26] "T cell mediated cytotoxicity"
## [27] "toll-like receptor signaling pathway"
## [28] "intrinsic apoptotic signaling pathway in response to endoplasmic reticulum stress"
## [29] "endoplasmic reticulum unfolded protein response"
## [30] "regulation of T cell mediated immunity"
## [31] "response to unfolded protein"
## [32] "cellular response to unfolded protein"
## [33] "regulation of response to endoplasmic reticulum stress"
## [34] "macrophage activation"
## [35] "response to topologically incorrect protein"
## [36] "acute inflammatory response"
## [37] "T cell mediated immunity"
## [38] "cellular response to topologically incorrect protein"
## [39] "chloride transport"
## [40] "homophilic cell adhesion via plasma membrane adhesion molecules"
## [41] "regulation of myeloid leukocyte differentiation"
## [42] "response to endoplasmic reticulum stress"
## [43] "viral entry into host cell"
## [44] "entry into host"
## [45] "myeloid leukocyte activation"
## [46] "positive regulation of inflammatory response"
## [47] "monoatomic anion transport"
## [48] "response to ketone"
## [49] "negative regulation of leukocyte activation"
## [50] "endothelial cell migration"Dotplot
Cnet plot
Molecular Signature Database (MSigDb)
The MSigDb is a collection of annotated gene sets. It contains 8 major collections:
- H : hallmark gene sets
- C1 : positional gene sets
- C2 : curated gene sets
- C3 : motifs gene sets
- C4 : computational gene sets
- C5 : GO gene sets
- C6 : oncogenic signatures
- C7 : immunologic signatures
- C8 : cell Type Signature
## gs_collection
## gs_collection_name C1 C2 C3 C4 C5
## BioCarta Pathways 0 11088 0 0 0
## Cancer Gene Neighborhoods 0 0 0 42623 0
## Cancer Modules 0 0 0 48830 0
## Canonical Pathways 0 579 0 0 0
## Cell Type Signature 0 0 0 0 0
## Chemical and Genetic Perturbations 0 442721 0 0 0
## Curated Cancer Cell Atlas gene sets 0 0 0 7390 0
## GO Biological Process 0 0 0 0 617648
## GO Cellular Component 0 0 0 0 103371
## GO Molecular Function 0 0 0 0 113119
## GTRD 0 0 257418 0 0
## Hallmark 0 0 0 0 0
## HIPC Vaccine Response 0 0 0 0 0
## Human Phenotype Ontology 0 0 0 0 530149
## ImmuneSigDB 0 0 0 0 0
## KEGG Legacy Pathways 0 12904 0 0 0
## KEGG Medicus Pathways 0 9688 0 0 0
## MIR_Legacy 0 0 34266 0 0
## miRDB 0 0 731405 0 0
## Oncogenic Signature 0 0 0 0 0
## PID Pathways 0 8062 0 0 0
## Positional 43883 0 0 0 0
## Reactome Pathways 0 108275 0 0 0
## TFT_Legacy 0 0 155547 0 0
## WikiPathways 0 40070 0 0 0
## gs_collection
## gs_collection_name C6 C7 C8 H
## BioCarta Pathways 0 0 0 0
## Cancer Gene Neighborhoods 0 0 0 0
## Cancer Modules 0 0 0 0
## Canonical Pathways 0 0 0 0
## Cell Type Signature 0 0 157573 0
## Chemical and Genetic Perturbations 0 0 0 0
## Curated Cancer Cell Atlas gene sets 0 0 0 0
## GO Biological Process 0 0 0 0
## GO Cellular Component 0 0 0 0
## GO Molecular Function 0 0 0 0
## GTRD 0 0 0 0
## Hallmark 0 0 0 7333
## HIPC Vaccine Response 0 44668 0 0
## Human Phenotype Ontology 0 0 0 0
## ImmuneSigDB 0 948621 0 0
## KEGG Legacy Pathways 0 0 0 0
## KEGG Medicus Pathways 0 0 0 0
## MIR_Legacy 0 0 0 0
## miRDB 0 0 0 0
## Oncogenic Signature 30753 0 0 0
## PID Pathways 0 0 0 0
## Positional 0 0 0 0
## Reactome Pathways 0 0 0 0
## TFT_Legacy 0 0 0 0
## WikiPathways 0 0 0 0Let’s see the results using different selections and using down regulated genes
## C3 : MIR_Legacy : 0 significant terms
## C3 : TFT_Legacy : 8 significant terms
## C2 : Chemical and Genetic Perturbations : 338 significant terms
## C3 : GTRD : 0 significant terms
## C8 : Cell Type Signature : 104 significant terms
## C6 : Oncogenic Signature : 19 significant terms
## C7 : HIPC Vaccine Response : 27 significant terms
## C2 : BioCarta Pathways : 0 significant terms
## C4 : Cancer Gene Neighborhoods : 0 significant terms
## C4 : Curated Cancer Cell Atlas gene sets : 7 significant terms
## C5 : GO Biological Process : 28 significant terms
## C5 : GO Cellular Component : 4 significant terms
## C7 : ImmuneSigDB : 308 significant terms
## C5 : GO Molecular Function : 1 significant terms
## H : Hallmark : 7 significant terms
## C5 : Human Phenotype Ontology : 0 significant terms
## C2 : KEGG Legacy Pathways : 0 significant terms
## C2 : KEGG Medicus Pathways : 1 significant terms
## C3 : miRDB : 0 significant terms
## C4 : Cancer Modules : 1 significant terms
## C1 : Positional : 0 significant terms
## C2 : PID Pathways : 0 significant terms
## C2 : Reactome Pathways : 9 significant terms
## C2 : Canonical Pathways : 0 significant terms
## C2 : WikiPathways : 9 significant terms- C6 : Oncogenic signatures
- C7 : Immunologic signatures
- C5 : GO Biological Process
- C8 : Cell Type Signature
- H : Hallmark
Gene Set Enrichment Analysis (GSEA)
GSEA is a functional class scoring method that evaluates whether predefined gene sets show statistically significant, concordant differences between two biological conditions. Unlike over-representation approaches, GSEA uses the entire ranked list of genes, avoiding the need for an arbitrary significance cutoff.
In this analysis, genes were ranked using a composite score based on both:
- the magnitude and direction of differential expression
(
log2FoldChange) - the statistical significance (
adjusted p-value,padj)
Interpretation of the ranking score
- High positive scores correspond to the most significant up-regulated genes
- High negative scores correspond to the most significant down-regulated genes
- Scores close to zero represent non-significant genes
The ranking score was computed according to the following rule:
ranking <- case_when(
abs(log2FoldChange) >= 3 & padj < 0.5 ~
round((sign(log2FoldChange) * 3) * (-log10(padj) / 10), 4),
abs(log2FoldChange) < 3 & padj < 0.5 ~
round(log2FoldChange * (-log10(padj) / 10), 4),
padj >= 0.5 ~ 0
)So basically
\[Score=log2(FC)×(−log10(padj))\]
Where beyond an absolute log2FoldChange value of 3, the
ranking metric is only driven by the statistical significance
padj.
Genes with padj ≥ 0.5 are assigned a score of zero,
effectively positioning them in the middle of the ranked list.
This scoring strategy allows a balanced integration of effect size and statistical confidence, making it suitable for downstream GSEA
For this analysis we going to use gene sets from the MSigDB (as already seen above)
- H : hallmark gene sets
- C5 : GO gene sets
- C6 : oncogenic signatures
Hallmarks
Below is the results represented in a dot plot
Now let’s view the enrichment plots
C5: GO gene sets
Below is the results represented in a dot plot
Now let’s view the enrichment plots
C6: oncogenic signatures
Below is the results represented in a dot plot
Now let’s view the enrichment plots
